Support for Enhanced GDPR Accountability with the Common Semantic Model for ROPA (CSM-ROPA)

Abstract

Abstract The creation and maintenance of Registers of Processing Activities (ROPA) are essential to meeting the General Data Protection Regulation (GDPR) and thus to demonstrate compliance based on the GDPR concept of accountability. To establish its effectiveness in meeting this obligation, we evaluate an ROPA semantic model, the Common Semantic Model–ROPA (CSM–ROPA). Semantic models and tools represent one solution to the compliance challenges faced by organisations: the heterogeneity of relevant data sources, and the lack of tool interoperability and agreed common standards. By surveying current practice and the literature we identify the requirements for GDPR accountability tools: digital exchange of data, automated accountability verification and privacy-aware data governance. A case study was conducted to analyse the expressivity and effectiveness of CSM–ROPA when used as an interoperable, machine-readable mediation layer to express the concepts in a comprehensive regulator-provided accountability framework used for GDPR compliance. We demonstrate that CSM–ROPA can express 98% of ROPA accountability terms and fully express nine of the ten European regulators' ROPA templates. We identify three terms for addition to CSM–ROPA, and we identify areas where CSM–ROPA relies on partial matches that indicate model limitations. These improvements to CSM–ROPA will provide comprehensive coverage of the regulator-supplied model. We show that tools based on CSM–ROPA can fully meet the requirements of compliance best practice when compared with either manual accountability approaches or a leading privacy software solution.

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